Pattern Analysis and Applications

27.9k citations
1.7k papers · · active since 1963

Impact in

Papers in

    • Image Retrieval and Classification Techniques 136
    • Face and Expression Recognition 123
    • Handwritten Text Recognition Techniques 114
    • Advanced Neural Network Applications 110
    • Medical Image Segmentation Techniques 96
    • Video Surveillance and Tracking Methods 91
    • Advanced Clustering Algorithms Research 99
    • Machine Learning and Data Classification 89

Pattern Analysis and Applications

1.5k papers receiving 26.5k citations

Peers

Pattern Analysis and Applications
Comparison fields: 5 of 205
  • Computer Vision and Pattern Recognition 10.4k
  • Signal Processing 2.1k
  • Artificial Intelligence 6.4k
  • Media Technology 698
  • Radiology, Nuclear Medicine and Imaging 1.7k
Replace International Journal of Pattern Recognition and Artificial Intelligence with:
International Journal of Pattern Recognition and Artificial Intelligence China
Multimedia Systems China
Neural Processing Letters China
Cognitive Computation China
Journal Of Big Data United States
IET Image Processing China
Artificial Intelligence in Medicine United States
ACM Transactions on Multimedia Computing Communications and Applications China
International Journal of Neural Systems China
International Journal of Machine Learning and Cybernetics China
Pattern Analysis and Applications relative to International Journal of Pattern Recognition and Artificial Intelligence China International Journal of Pattern Recognition and Artificial Intelligence's profile →
Citations per field
00.5×1.5×2×2.5×
International Journal of Pattern Recognition and Artificial Intelligence · 1×
Citations per year

Countries where authors publish in Pattern Analysis and Applications

Since Specialization
Citations

This map shows the geographic impact of research published in Pattern Analysis and Applications. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Pattern Analysis and Applications with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pattern Analysis and Applications more than expected).

Fields of papers published in Pattern Analysis and Applications

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Pattern Analysis and Applications. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Pattern Analysis and Applications.

About Pattern Analysis and Applications

The 1.7k papers published in Pattern Analysis and Applications in the last decades have received a total of 27.9k indexed citations . Papers published in Pattern Analysis and Applications usually cover Computer Vision and Pattern Recognition (885 papers), Artificial Intelligence (486 papers), Signal Processing (105 papers), Computational Mathematics (3 papers) and Media Technology (38 papers) specifically the topics of Image Retrieval and Classification Techniques (136 papers), Face and Expression Recognition (123 papers), Handwritten Text Recognition Techniques (114 papers), Advanced Neural Network Applications (110 papers), Advanced Clustering Algorithms Research (99 papers), Medical Image Segmentation Techniques (96 papers), Video Surveillance and Tracking Methods (91 papers) and Machine Learning and Data Classification (89 papers). The most active scholars publishing in Pattern Analysis and Applications are Ali Narin, Ziynet Pamuk, Josef Kittler, Robert P. W. Duin, Adnan Amin, Marina Skurichina, Neil Yager, Li Bai, Linlin Shen and M. S. Khorsheed.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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